Electromagnetic Simulation Makes Connections with the US DoD’s JADC2 Implementation
Everyone who uses a cell phone may not realize that the electromagnetic spectrum that allows for connection to the network is regulated by governments around the world. In the United States, much of the bandwidth for modern networks has been released from exclusive use by the Department of Defense (DoD). Those discrete bands of frequencies were auctioned off to private entities over the course of several years to form the basis of 4G and 5G networks. To enable those auctions, the DoD began studying ways that it could use fewer rigid methods to allocate spectrum, which is a band of frequencies used for radio frequency (RF) communications, radars, and sensing. By developing new policies and procedures, they opened the door to allocate spectrum for operations by individual DoD branch entities in a more agile and dynamic manner.
The U.S. DoD would like to take advantage of the ability to remain always-connected and benefit its operations in-theater. Ironically, the ability to be more agile with spectrum management that was set in motion by the process of the DoD giving up exclusive ownership of spectral bands for commercial use has opened the possibility of even more capable spectrum operations to support a new DoD initiative. Electromagnetic simulation will play a key role in the success of the initiative. Its impact will be felt as the technologies are developed and again as the DoD seeks to speed up the acquisition of enabling hardware.
JADC2 and Spectrum Operations
The DoD’s Joint All-Domain Command and Control (JADC2) initiative is about rapidly fielding new capabilities and tools across multiple domains — which include land, sea, air, and cyber — across multiple service branches. JADC2 is implementing the connectivity of many systems, doing so in a joint fashion, across everything that the U.S. DoD does to help make faster and better decisions in the field. That connectivity will ultimately involve the electromagnetic spectrum in nearly every aspect of its implementation.
“With respect to spectrum: we sense, we communicate, and then try to prevent adversaries from doing those first two things,” says Joshua Weaver, Director of Spectrum Initiatives and Analysis at the Office of the Under Secretary of Defense for Research and Engineering. “The goal of JADC2 is to be able to move sensor data to the commander to build that common operating picture and ultimately reduce the latency to decision and action to achieve the desired effects.”
What makes achieving the JADC2 spectrum operations goals so challenging are the small amounts of time required to do complex tasks. For example, decisions that previously took days now must be made in hours or minutes. Those challenges are both technical and procedural. On the technical side, it becomes a big data problem, where the size of data that must be moved is immense. We have all experienced bad data links that prevent us from connecting to the internet. For DoD, there is the additional complication that there is an adversary that is actively working to break their network connectivity. Electromagnetic modeling of the link is a critical technology to accurately predict connectivity.
On the procedural side, decisions are made at infrastructure far from forward operation after careful deliberations by people in a defined chain of command. Those decisions are based on rigid rules and guided by testing or analysis performed years or decades ago. To speed those decisions from days to minutes, both the technology and the bureaucratic processes must evolve. Electromagnetic simulation combined with machine learning (ML) techniques will be an important part of making faster decisions.
Dynamic Spectrum Operations
The roadmap for future military systems must consider the fact that the amount of electromagnetic spectrum is finite. In the past, advanced militaries defined their spectrum use and developed their systems using a very long procurement cycle. Potential adversaries might have chosen to exploit this lack of flexibility and implement their own use of spectrum management that is more agile and adaptable. That is why JADC2 places an emphasis on a system of dynamic spectrum operations.
“Agile electromagnetic spectrum operations will leverage modernized, networked command, control, and communication systems and support electromagnetic spectrum superiority, which in turn enables JADC2 operations,” according to the U.S. Defense Spectrum Organization’s Electromagnetic Spectrum Enterprise Capabilities and Services Booklet.
However, with agility comes risk. But spectrum can be allocated, and risk can be managed in other ways besides giving exclusive use of parts of the spectrum to specific industry sectors. Electromagnetic simulation allows interference risks to be quantified so that good spectrum management decisions can be made.
Lastly, we must consider the fact that the new hardware cannot be fielded immediately. There is a clear process that must be followed in acquisition. It is easy to find stories of commercial equipment that was placed in a military environment and immediately ceased functioning or degraded the performance of other equipment. As a result, a risk-based approach to verification of electromagnetic effects during acquisition is required to allow new technologies to be fielded quickly but in such a way as to minimize interference that could be catastrophic. Electromagnetic simulation is the key to quantifying the risk and ensuring a high likelihood of compatibility.
Industry’s Role in Link Modeling
“There’s a need for digital engineering and simulation at the platform level including spectrum effects or communication effects,” says Regina Tyrrell of the U.S. Army Program Executive Office for Simulation, Training, and Instrumentation (PEO STRI). “It’s an area that is ripe for development and maturation.”
The goals of JADC2 require close partnership between government and industry. Fortunately, new technologies are emerging to allow for faster evaluation of risk to allow for greater agility. These methods use first-principle simulation technologies coupled with artificial intelligence (AI) and ML to achieve the speed and accuracy necessary to make good decisions faster or even automatically.
The first way that simulation can provide support is in understanding data links. Ansys Systems Tool Kit (STK) can be used to model scenarios with multiple platforms, each with RF systems, and their dynamics through space and time to predict link quality. This product is directly coupled to Ansys Electronics Desktop, which allows for link analysis in a range of scenarios. Accurate modeling is needed to provide information on the link performance. This is no longer simply about whether the link is up or not. JADC2 requires communications and data exchanges that are resilient, preferably with multiple paths that can gracefully degrade. This can only be predicted with highly accurate link modeling. Prediction is essential to make good decisions about which frequencies should be used in each domain. Figure 1 shows installed antenna patterns computed by Ansys Electronics Desktop for military aircraft.
Figure 1a. Installed antenna radiation patterns as computed with Ansys Electronics Desktop
Figure 1b. Installed antenna radiation patterns as computed with Ansys Electronics Desktop
The goal is to use digital engineering to create scenarios and link models that are an analog to what happens in the physical environment, which will ultimately be translated into risk scores to aid in fast decision making. Spectrum managers will use digital engineering to inform their decisions. Implementation of their decisions is made via control messages sent to hardware in the environment to change frequency, change modulation, change location, or cease transmitting. The radios collect link information to course correct in real time or provide data sets to test simulation accuracy. Thus, simulation may be refined to allow it to improve over time.
Modeling in electromagnetics has improved to the point where it can be accurate for military scenarios. The frontier in spectrum management is in combining the physics solvers with AI/ML techniques to allow for faster scenario evaluation. The timescales of JADC2 do not allow for six months of computational studies that are then validated by another six months of field testing. Instead, simulation provides inputs to AI/ML model training that provides risk-based scores accurately and quickly. The initial result may be augmented by real-time sensor data that further improves the accuracy and grounds it in the operational truth.
Industry’s Role in Acquisition and Ensuring Compatibility
Each service has its own acquisitions programs. They will continue to procure spectrum-dependent systems. Acquisition and compatibility considerations are key challenges standing between having the new operational initiatives demonstrated versus implementing them in joint operations. The current approach is to follow MIL-STD-461 testing with the assumption that operational frequencies are static. There are two drawbacks to this approach. The first is the fact that there are gaps in the MIL-STD-461 approach that will become more challenging in a more agile spectrum environment. The second is the amount of time required to complete a full MIL-STD-461 development and verification in a standard acquisition environment.
Improve Radio Frequency Interference Analysis
Even if a unit meets MIL-STD-461 requirements for emissions or susceptibility, compatibility is not automatically guaranteed. The appendix for 461 is very clear about this. Even if all RF systems meet the 461 requirements, primes must perform an RF interference analysis given the proximity of these systems and all other items that can be added to the RF architecture including filters, amplifiers, cables, and directional antennas.
Department of Defense Form 1494 (DD 1494) is standard for all RF systems. When combined with scenario modeling and link analysis, it should allow for the accurate prediction of unwanted interference. The problem is that the data in DD 1494 is often not accurate or complete.
A solution to the inaccuracy in the data on DD 1494s is to quickly improve the fidelity of RF system receiver and transmitter information. New technologies that automate the collection of the out-of-band RF system performance are available. One example is the Automated Radio Measurement System (ARMS), which combines off-the-shelf test equipment, custom filter banks, and automation software to improve the speed of accurate data collection by two orders of magnitude.
Automation is also essential for RF systems that operate over many channels, modulations, and power levels. Some modern military RF systems can support tens of thousands and sometimes a few hundred thousand channels. Manually measuring the performance of even a subset of so many channels involves a large cost and time commitment. With ARMS, the user can program the channels, modulation, and power levels that they wish to measure, click “Run” and walk away until the measurements are complete.
ARMS is also capable of measuring the wideband susceptibility of a receiver. For a susceptibility measurement, the intended signal is injected into the receiver and a baseline performance metric is established. Then an interfering signal is simultaneously injected out-of-band and the performance metric is monitored for degradation. With this approach, one can characterize the susceptibility of a receiver as a function of frequency as shown in Figure 2. In this example, the measured selectivity of the receiver is much broader than stated on the receiver specification sheet and there is a spurious response near 1.28 GHz that is not captured on the receiver specification sheet.
Figure 2. A comparison between measured data and a specification sheet for the wideband performance of a GNSS receiver
Using measured RF system data from ARMS in simulation tools such as Ansys EMIT dramatically improves the accuracy of RF interference analyses. As can be seen in Figure 2, specification sheets and DD 1494s can be wildly inaccurate with regards to the wideband performance of the RF systems. Without measured data, it is often a garbage-in, garbage-out scenario when it comes to predicting RF interference. A typical RF interference scenario as modeled in EMIT is shown in Figure 3.
Figure 3. EMIT requires wideband data for all of the components found in RF architectures as well as the antenna-to-antenna coupling.
For RF interference simulations, you need wideband data for all of the components in the RF architecture (e.g., filters, cables, amplifiers, etc.), the antenna-to-antenna coupling, and the RF systems. Vendors are increasingly providing measured or simulated scattering parameters(S-parameters) for filters, cables, and other components. When data is not available from vendors, tools such as Ansys Nuhertz and Ansys Nexxim can be used to simulate performance. It is also possible to predict the antenna-to-antenna coupling using tools such as Ansys HFSS and SBR+. So, you can see how through the combination of powerful simulation tools from Ansys and measured data from ARMS that all of the necessary input data for RF interference simulations is possible.
DoD Directive 5000.01 guides the U.S. Defense Acquisition System policies and procedures. The directive gives a clear ability to waive requirements to meet faster procurement cycles, but a wholesale removal of interference compatibility analysis would negate the benefits of choosing to proceed with agile spectrum operations. Instead, a risk-based approach would allow for the logical tailoring of electromagnetic compatibility and electromagnetic environmental effects requirements using physics-based engineering simulation.
Ansys EMC Plus (formerly Ansys EMA3D Cable) enables engineers to predict electromagnetic compatibility effects at the platform and equipment levels. It provides quick and efficient conversion of 3D computer-aided design (CAD) to an EM model of the entire vehicle. Thus, EM teams can maintain a virtual EM test environment that is traceable and is useful to predict the integrated vehicle performance with respect to several EM requirements and environments.
The full-vehicle model is helpful to determine the level of tailoring that is acceptable to maintain compatibility and a low-risk path to meeting vehicle-level requirements. Examples of EM virtual testing tasks include:
- EMC requirements per MIL-STD-461 and DO-160
- E3 requirements for lightning SAE ARP5415 or ARP5416
- E3 requirements for high intensity radiated fields (HIRF) per SAE ARP5583
- Electromagnetic interference (EMI) and intrasystem compatibility of the platform Ansys EMC Plus can model complex electrical wiring interconnect system cables that have over braids, shields, multiple conductors, branches, and terminations. It enables engineers to specify 3D routing of the cables from the CAD document. Then, engineers can specify the shields and conductors by importing the harness connectivity from wiring database software. Design information from CAD, wiring diagrams, and other sources are efficiently converted into an EMC Plus virtual test environment model.
Engineers can create models of entire vehicles in a reasonable time and determine if requirements may be safely relaxed or tailored.
Simulation is Key to Connectivity
We enjoy modern connectivity that is robust and ever-present due to spectrum management and spectrum sharing. DoD is moving toward a new paradigm to achieve robust and agile connectivity, even in a contested environment.
Electromagnetic effects and spectrum management are essential parts of DoD’s new JADC2 initiative. For the new initiative to be successful, electromagnetic modeling, simulation, and testing will play a key role in the transition. This includes new simulation technologies to support link modeling, to include AI/ML to speed results. It will also require interference analysis and testing to include better characterization of radio out-of-band characteristics. Finally, EMC simulation of full platforms and equipment are needed to allow for accelerated procurement through careful tailoring of electromagnetic requirements to maintain mission success.
This article was originally published in Ansys Advantage.